Dataset from: Towards Global Parameter Estimation Exploiting Reduced Data Sets

Saß, Susanne; Tsoukalas, Angelos; Bell, Ian H.; Najman, Jaromil; Bongartz, Dominik; Mitsos, Alexander

doi:10.18154/RWTH-2022-03252

Dataset from: Towards Global Parameter Estimation Exploiting Reduced Data Sets

Saß, Susanne^RWTH* ; Tsoukalas, Angelos ; Bell, Ian H. ; Bongartz, Dominik^RWTH* ; Najman, Jaromil^RWTH* ; Mitsos, Alexander^RWTH*

2023

Online
DOI: 10.18154/RWTH-2022-03252
URL: https://publications.rwth-aachen.de/record/843599/files/ModelFiles_and_Results.zip

Einrichtungen

Lehrstuhl für Systemverfahrenstechnik (416710)

Projekte

GRK 2379 - GRK 2379: Hierarchische und hybride Ansätze für moderne inverse Probleme (333849990) (333849990)

Inhaltliche Beschreibung (Schlagwörter)
Deterministic global optimization (frei) ; MINLP (frei) ; parameter estimation (frei) ; B&B algorithm (frei) ; Equation of state (frei)

Kurzfassung
We focus on deterministic global optimization (DGO) for nonconvex parameter estimation problems. Realistic and accurate solutions often require a fitting against very large measurement data sets, resulting in intractable size for DGO. Thus, we aim at accelerating the branch-and-bound algorithm by using reduced data sets for constructing valid bounds. We focus on fitting the equation of state for propane, which is of high interest for the chemical industry. The resulting estimation problem is a challenging nonconvex mixed-integer nonlinear optimization problem. We investigate the validity of using reduced data sets by comparing how the lower and upper bounds change when replacing the full data set with different reduced data sets. We account for regions with high and low quality fits by considering the results for the whole feasible region and 100 different subregions. Our results indicate that both regions containing solution candidates and regions containing only low quality fits can be identified based on reduced data sets. Moreover, we observe that the average CPU time per branch-and-bound iteration typically decreases if reduced data sets are used.

OpenAccess:
ZIP
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